Image processing device, imaging device and image processing method
An image processing device and image processing technology, which are applied in the directions of image data processing, image data processing, image enhancement, etc., can solve the problems of depth data accuracy decline, achieve the effect of reducing processing load and suppressing the decline of accuracy
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Embodiment approach 1
[0061] figure 1 It is a block diagram showing the functional configuration of the image processing apparatus 10 according to the first embodiment. The image processing device 10 generates depth data of the first image using a first image and a second image (for example, a stereo image) taken from different viewpoints. The first image and the second image are, for example, stereo images (an image for the left eye and an image for the right eye).
[0062] Such as figure 1 As shown, the image processing device 10 according to this embodiment includes a parallax value calculation unit 11, a segmentation unit 12, and a depth data generation unit 13.
[0063] The parallax value calculation unit 11 detects the corresponding pixel in the second image for each representative pixel in the first image, and thereby calculates the parallax value between the representative pixel and the corresponding pixel. That is, the parallax value calculation unit 11 calculates a parallax value for some pix...
Embodiment approach 2
[0083] Next, Embodiment 2 will be described with reference to the drawings.
[0084] Figure 4 It is a block diagram showing the functional configuration of the image processing apparatus 20 according to the second embodiment. The image processing device 20 according to this embodiment includes a feature point calculation unit 21, an alignment processing unit 22, a parallax value calculation unit 23, a segmentation unit 24, a segment combination unit 25, a depth data generation unit 26, and an image processing unit 27.
[0085] The feature point calculation unit 21 calculates feature points of the first image as representative pixels. Specifically, the feature point calculation unit 21 calculates feature points using the feature amount extracted by the feature amount extraction method. As the feature extraction method, for example, it can be used in Reference 1 (David G. Lowe, "Distinctive image features from scale-invariant keypoints", International Journal of Computer Vision, 6...
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